Non-specific binding and steric hindrance thresholds for penetration of particulate drug carriers within tumor tissue

Abstract

Therapeutic nanoparticles (NPs) approved for clinical use in solid tumor therapy provide only modest improvements in patient survival, in part due to physiological barriers that limit delivery of the particles throughout the entire tumor. Here, we explore the thresholds for NP size and surface poly(ethylene glycol) (PEG) density for penetration within tumor tissue extracellular matrix (ECM). We found that NPs as large as 62nm, but less than 110nm in diameter, diffused rapidly within a tumor ECM preparation (Matrigel) and breast tumor xenograft slices ex vivo. Studies of PEG-density revealed that increasing PEG density enhanced NP diffusion and that PEG density below a critical value led to adhesion of NP to ECM. Non-specific binding of NPs to tumor ECM components was assessed by surface plasmon resonance (SPR), which revealed excellent correlation with the particle diffusion results. Intravital microscopy of NP spread in breast tumor tissue confirmed a significant difference in tumor tissue penetration between the 62 and 110nm PEG-coated NPs, as well as between PEG-coated and uncoated NPs. SPR assays also revealed that Abraxane, an FDA-approved non-PEGylated NP formulation used for cancer therapy, binds to tumor ECM. Our results establish limitations on the size and surface PEG density parameters required to achieve uniform and broad dispersion within tumor tissue and highlight the utility of SPR as a high throughput method to screen NPs for tumor penetration.

Keywords: Intravital microscopy; Multiple particle tracking (MPT); Nanoparticles; PEG density; Surface plasmon resonance (SPR); Tumor tissue penetration.

Figure 1. Diffusion of nanoparticles of different sizes in Matrigel

The diffusion of individual fluorescent polystyrene (PS) NPs in Matrigel was quantified using multiple particle tracking (MPT). (A) Ensemble-averaged mean square displacements (MSD) as a function of time scale for 20, 40, and 100 nm uncoated (UNP) and PEG coated (CNP) PS NPs. (B) The ensemble-averaged MSD of nanoparticles at a time scale of 1 s. (C) Distributions of the logarithms of individual MSDs for UNPs and CNPs of different sizes at a time scale of 1 s. Larger MSD values indicate faster transport rates of nanoparticles. Data represents at least three experiments, with n ≥ 100 particles per experiment. **P ≤ 0.01.

Figure 2. Diffusion of nanoparticles of different sizes in MDA-MB-231 tumor tissue ex vivo

MDA-MB-231 breast cancer cells were injected into the flank of mice and tumors were allowed to grow to ~500 mm³. Tumor slices were prepared, fluorescent NPs were injected into the tumor, and the diffusion of individual NPs was quantified using multiple particle tracking (MPT). For these experiments, the transport rates of all three particle sizes, with and without PEG coatings, were measured in the same tumor tissue. (A) Ensemble-averaged mean square displacements (MSD) as a function of time scale. (B) The ensemble-averaged MSD of nanoparticles at a time scale of 1 s. (C) Distributions of the logarithms of individual MSDs for UNPs and CNPs of different sizes at a time scale of 1 s. Data represents at least three experiments, with n ≥ 100 particles per experiment. *P < 0.05, **P ≤ 0.01.

Figure 3. Surface plasmon resonance (SPR) analysis of 40 nm nanoparticles with varying surface PEG densities

SPR experiments were performed by flowing various NP formulations into flow cells and across the surface of a Matrigel-coated sensor chip. Data is displayed as sensograms showing resonance units (RU) as a function of time. (A) SPR analysis measuring the binding of 40 nm uncoated (UNP) and coated (CNP) nanoparticles ranging in PEG-coating densities (low, medium, high) to a Matrigel chip. (B) Expanded view of boxed region in A.

Figure 4. Diffusion of nanoparticles with varying PEG densities in Matrigel

The diffusion of individual fluorescent NPs that were either uncoated or coated with a low, medium, or high PEG density in Matrigel was quantified using multiple particle tracking (MPT). (A) Ensemble-averaged mean square displacements (MSD) as a function of time scale. (B) The ensemble-averaged MSD of nanoparticles at a time scale of 1 s. Data represents at least three experiments, with n ≥ 100 particles per experiment. **P ≤ 0.01.

Figure 5. Diffusion of nanoparticles with varying PEG densties in MDA-MB-231 tumor tissue ex vivo

MDA-MB-231 bresat cancer cells were injected into the flank of mice and tumors were allowed to grow to ~ 500 mm³. Tumor slices were prepared and the diffusion of individual fluorescent NPs was quantified using multiple particle tracking (MPT). (A) Ensemble-averaged mean square displacements (MSD) as a function of time scale. (B) The ensemble-averaged MSD of nanoparticles at a time scale of 1 s. Data represents at least three experiments, with n ≥ 100 particles per experiment. *P < 0.05, **P ≤ 0.01.

Figure 6. Nanoparticle penetration of breast tumor tissue in vivo

MDA-MB-231 breast cancer cells were injected into the flank of mice and tumors were allowed to grow to ~ 500 mm³. Fluorescent nanoparticle formulations were injected at a depth of 100–200 μm and particle distribution within the tumor was assessed by 2-photon confocal microscopy. (A) Direct comparison of the distribution of fluorescent uncoated and PEG coated 40 nm PS NPs after direct tumor co-injection into mice. Images were acquired within 10 minutes after injection. (B) Direct comparison of the distribution of PEG-coated 100 nm PS NPs (100 nm CNP) and uncoated 40 nm PSCOOH NPs (40 nm UNP). Images were acquired within 10 minutes after injection. Arrow indicates approximate postion of injection needle. Scale bar is 500 μm.

Figure 7. Surface plasmon resonance (SPR) analysis of biodegradable nanoparticles

SPR experiments were performed by flowing various NP formulations into flow cells and across the surface of a Matrigel-coated sensor chip. Data is displayed as sensograms showing resosnance units (RU) as a function of time. (A) SPR analysis measuring the binding of PLGA and PEG-PLGA nanoparticles ranging in PEG-coating percentages (1%, 2.5%, 5%) to a Matrigel chip. (B) Expanded view of boxed region in A. (C) Screening of the FDA-approved nanodrugs Abraxane and Doxil for non-specific binding to tumor ECM. Data was compiled from separate runs using the same Matrigel chip.